Sakari Jukarainen1, René Holst2,3, Christine Dalgård4,5, Päivi Piirilä6, Jesper Lundbom7,8, Antti Hakkarainen7, Nina Lundbom7, Aila Rissanen1, Jaakko Kaprio9,10, Kirsten Ohm Kyvik11,12,5, Thorkild I A Sørensen13,14,15, Kirsi H Pietiläinen1,16. 1. Obesity Research Unit, Research Programs Unit, Diabetes and Obesity, University of Helsinki, 00290 Helsinki, Finland. 2. Institute of Regional Health Service Research, University of Southern Denmark, 5230 Odense, Denmark. 3. Oslo Centre for Biostatistics and Epidemiology, University of Oslo and Oslo University Hospital, 0313 Oslo, Norway. 4. Department of Public Health - Environmental Medicine, University of Southern Denmark, 5230 Odense, Denmark. 5. Danish Twin Registry, University of Southern Denmark, 5230 Odense, Denmark. 6. Unit of Clinical Physiology, Helsinki University Hospital and University of Helsinki, Meilahti Hospital, 00290 Helsinki, Finland. 7. Helsinki Medical Imaging Center, Radiology, University of Helsinki, 00290 Helsinki, Finland. 8. Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research, Heinrich Heine University, 40225 Düsseldorf, Germany. 9. Department of Public Health, University of Helsinki, 00300 Helsinki, Finland. 10. Institute for Molecular Medicine Finland, University of Helsinki, 00290 Helsinki, Finland. 11. Odense Patient Data Explorative Network, Odense University Hospital, 5000 Odense, Denmark. 12. Department of Clinical Research, University of Southern Denmark, 5200 Odense, Denmark. 13. Novo Nordisk Foundation Center for Basic Metabolic Research, Section on Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark. 14. Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark. 15. Department of Clinical Epidemiology (formerly Institute of Preventive Medicine), Bispebjerg and Frederiksberg Hospitals, The Capital Region, 2400 Copenhagen, Denmark. 16. Endocrinology, Abdominal Center, Helsinki University Central Hospital and University of Helsinki, 00290 Helsinki, Finland.
Abstract
Context: The joint effects of cardiorespiratory fitness (CRF) and body composition on metabolic health are not well known. Objective: To examine the associations of CRF, fat-free mass index (FFMI), and fat mass index (FMI) with metabolic health in individual twins and controlling for genetic and shared environmental effects by studying monozygotic intrapair differences. Design, Setting, and Participants: Two cross-sectional samples of healthy adult monozygotic and dizygotic twins were drawn from population-based Danish and Finnish national twin registries (n = 996 and n = 309). Main Measures: CRF was defined as VO2max divided by fat-free mass. Insulin sensitivity and acute insulin response indices were derived from an oral glucose tolerance test. A continuous metabolic syndrome score was calculated. Visceral and liver fat were measured in the Finnish sample. Associations were analyzed separately in both cohorts with multivariate linear regression and aggregated with meta-analytic methods. Results: Insulin sensitivity, acute insulin response, metabolic syndrome score, visceral, and liver fat amount had strong and statistically significant associations with FMI (|β| 0.53 to 0.79), whereas their associations with CRF and FFMI were at most weak (|β| 0.02 to 0.15). The results of the monozygotic intrapair differences analysis showed the same pattern. Conclusions: Although FMI is strongly associated with worsening of metabolic health traits, even after controlling for genetic and shared environmental factors, there was little evidence for the effects of CRF or FFMI on metabolic health. This suggests that changing FMI rather than CRF or FFMI may affect metabolic health irrespective of genetic or early environmental determinants.
Context: The joint effects of cardiorespiratory fitness (CRF) and body composition on metabolic health are not well known. Objective: To examine the associations of CRF, fat-free mass index (FFMI), and fat mass index (FMI) with metabolic health in individual twins and controlling for genetic and shared environmental effects by studying monozygotic intrapair differences. Design, Setting, and Participants: Two cross-sectional samples of healthy adult monozygotic and dizygotic twins were drawn from population-based Danish and Finnish national twin registries (n = 996 and n = 309). Main Measures: CRF was defined as VO2max divided by fat-free mass. Insulin sensitivity and acute insulin response indices were derived from an oral glucose tolerance test. A continuous metabolic syndrome score was calculated. Visceral and liver fat were measured in the Finnish sample. Associations were analyzed separately in both cohorts with multivariate linear regression and aggregated with meta-analytic methods. Results: Insulin sensitivity, acute insulin response, metabolic syndrome score, visceral, and liver fat amount had strong and statistically significant associations with FMI (|β| 0.53 to 0.79), whereas their associations with CRF and FFMI were at most weak (|β| 0.02 to 0.15). The results of the monozygotic intrapair differences analysis showed the same pattern. Conclusions: Although FMI is strongly associated with worsening of metabolic health traits, even after controlling for genetic and shared environmental factors, there was little evidence for the effects of CRF or FFMI on metabolic health. This suggests that changing FMI rather than CRF or FFMI may affect metabolic health irrespective of genetic or early environmental determinants.
Authors: Yi Ying Ong; Jonathan Y Huang; Navin Michael; Suresh Anand Sadananthan; Wen Lun Yuan; Ling-Wei Chen; Neerja Karnani; S Sendhil Velan; Marielle V Fortier; Kok Hian Tan; Peter D Gluckman; Fabian Yap; Yap-Seng Chong; Keith M Godfrey; Mary F-F Chong; Shiao-Yng Chan; Yung Seng Lee; Mya-Thway Tint; Johan G Eriksson Journal: J Clin Endocrinol Metab Date: 2021-04-23 Impact factor: 5.958
Authors: Enrique Albert Pérez; Marina Poveda González; Rosa María Martínez-Espinosa; Mariola D Molina Vila; Manuel Reig García-Galbis Journal: Int J Environ Res Public Health Date: 2019-09-18 Impact factor: 3.390